title: Improved detection of landmarks on 3D human face data.
abstract: Craniofacial researchers make heavy use of established facial landmarks in their morphometric analyses. For studies on very large facial image datasets, the standard approach of manual landmarking is very labor intensive. With the goal of producing 20 established landmarks, we have developed a geometric methodology that can automatically locate 10 established landmark points and 7 other supporting points on human 3D facial scans. Then, to improve accuracy and produce all 20 landmarks, a deformable matching procedure establishes a dense correspondence from a template 3D mesh with a full set of 20 landmarks to each individual 3D mesh. The 17 geometrically-determined points on the individual 3D mesh are used for the initial correspondence required by the deformable matching. The method is evaluated on 115 3D facial meshes of normal adults, and results are compared to landmarks manually identified by medical experts. Our results show a marked improvement to prior results in the recent literature.
authors.forename: Shu
authors.initials: S
authors.lastname: Liang
authors.forename: Jia
authors.initials: J
authors.lastname: Wu
authors.forename: Seth M
authors.initials: SM
authors.lastname: Weinberg
authors.forename: Linda G
authors.initials: LG
authors.lastname: Shapiro
mesh_terms: D000328:Adult; D000465:Algorithms; D000886:Anthropometry; D001331:Automation; D005145:Face / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results